One of the main causes of death the world over are cardiovascular diseases, of which coronary artery disease (CAD) is a major type. This disease occurs when the diameter narrowing of one of the left anterior descendin...
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ISBN:
(纸本)9780769549255;9781467351645
One of the main causes of death the world over are cardiovascular diseases, of which coronary artery disease (CAD) is a major type. This disease occurs when the diameter narrowing of one of the left anterior descending, left circumflex, or right coronary arteries is equal to or greater than 50 percent. Angiography is the principal diagnostic modality for the stenosis of heart vessels;however, because of its complications and costs, researchers are looking for alternative methods such as data mining. This study conducts data mining algorithms on the Z-Alizadeh Sani dataset which has been collected from 303 random visitors to Tehran's Shaheed Rajaei Cardiovascular, Medical and Research Center. In this paper, the reason of effectiveness of a preprocessing algorithm on the dataset is investigated. This algorithm which has been merely introduced in our previous works, extracts three new features from the dataset. These features are then used to enrich the primary dataset in order to achieve more accurate results. Moreover, despite the fact that misclassification of diseased patients has more side effects than that of healthy ones, to the best of our knowledge cost-sensitive algorithms have yet to be used in this field. Therefore, in this paper 10-fold cross validation on cost-sensitive algorithms along with base classifiers of naivebayes, Sequential Minimal Optimization (SMO), K-Nearest Neighbors (KNN), Support Vector Machine (SVM), and C4.5 were employed. As a result, the SMO algorithm has yield to very high sensitivity (97.22%) and accuracy (92.09%) rates, the likes of which have not been reported simultaneously in the existing literature.
Instead of the expansion of the information retrieval systems, the music information retrieval domain is still an open one. One of the promising areas in this context is the audio indexing databases. This paper addres...
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ISBN:
(纸本)9789898425799
Instead of the expansion of the information retrieval systems, the music information retrieval domain is still an open one. One of the promising areas in this context is the audio indexing databases. This paper addresses the problem of indexing database containing songs to enable their effective exploitation. Since, we are interested with songs databases, it is necessary to exploit the specific structure of the song in with each part plays a specific role. We propose to use the title and the artist particularities (in fact each artist tends to compose or sing a specific genre of music). In this article, we present our experiments in automated song categorisation, where we suggest the use of an ant colony algorithm. A naive bayes algorithm is used as a baseline in our tests.
Energy-efficient communication protocols in resource-constrained networks and specifically wireless body area networks (WBANs) has been of significant importance since they emerged nearly last decade. In this work, we...
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ISBN:
(纸本)9781457713484
Energy-efficient communication protocols in resource-constrained networks and specifically wireless body area networks (WBANs) has been of significant importance since they emerged nearly last decade. In this work, we use the periodic nature of body actions to propose an action-based scheduling technique in which time-slot allocations are adapted to the periodic connectedness of on-body links. In other words, the periodicity of on-body links is employed to predict the future behaviours of links to help develop energy-efficient communications between on-body nodes, thereby elongating the network lifetime. Analysis and measurement with 2.4GHz IEEE 802.15.4/ZigBee compliant micaZ motes in a fitness environment serve as our tool to do action recognition and subsequently scheduling. The proposed technique helps us reach within less than 7% of power consumption lower bound while it does not have complexity of most channel prediction algorithms that can result in excessive process power consumption.
Energy-efficient communication protocols in resource-constrained networks and specifically wireless body area networks (WBANs) has been of significant importance since they emerged nearly last decade. In this work, we...
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ISBN:
(纸本)9781457713460
Energy-efficient communication protocols in resource-constrained networks and specifically wireless body area networks (WBANs) has been of significant importance since they emerged nearly last decade. In this work, we use the periodic nature of body actions to propose an action-based scheduling technique in which time-slot allocations are adapted to the periodic connectedness of on-body links. In other words, the periodicity of on-body links is employed to predict the future behaviours of links to help develop energy-efficient communications between on-body nodes, thereby elongating the network lifetime. Analysis and measurement with 2.4GHz IEEE 802.15.4/ZigBee compliant micaZ motes in a fitness environment serve as our tool to do action recognition and subsequently scheduling. The proposed technique helps us reach within less than 7% of power consumption lower bound while it does not have complexity of most channel prediction algorithms that can result in excessive process power consumption.
According to the current research status of component retrieval, the component description model based on facet classification is improved by adding semantic features. Furthermore, the component retrieval process mode...
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According to the current research status of component retrieval, the component description model based on facet classification is improved by adding semantic features. Furthermore, the component retrieval process model is put forward by combining the domain ontology with the relative concept match algorithm. A detailed illustration of a component reasoning engine and a component classification engine is given and the component classification algorithm is provided by using the naive bayes algorithm based on domain ontology. The experimental results show that the recall ratio and the precision ratio are obviously improved by using the method based on semantics, and demonstrate the feasibility and effectiveness of the proposed method.
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